
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "180"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 158 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 153 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	56.22%	100.00%	0.00%	100.00%	0.00%	1.565335	14.145648	2.749547	81.126658	14.315317	27.880590	10.043927	32.909892	0.4087	0.0818	0.2015	3.718590	2.226427
2459593	RF_maintenance	100.00%	59.43%	100.00%	0.00%	100.00%	0.00%	36.725866	18.441952	7.389779	86.393089	21.008053	38.060490	8.079052	11.556266	0.3744	0.0757	0.1802	4.117475	1.882100
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	1.379777	1.536668	1.599026	7.867035	3.355811	1.339914	-1.841619	0.264737	0.0412	0.0328	-0.0009	nan	nan
2459591	RF_maintenance	100.00%	94.05%	100.00%	0.00%	100.00%	0.00%	50.534692	21.882547	11.975807	100.238686	21.346195	32.180050	-0.846108	1.915538	0.2923	0.0744	0.1394	1.888959	1.143421
2459590	RF_maintenance	100.00%	92.97%	100.00%	0.00%	100.00%	0.00%	51.968116	25.197767	10.664167	93.382486	15.772782	34.558537	-0.702766	3.469758	0.2875	0.0741	0.1360	1.809645	1.225613
2459589	RF_maintenance	100.00%	81.58%	100.00%	0.00%	100.00%	0.00%	50.116213	22.731224	9.422321	86.540311	15.005777	21.994807	12.274243	17.078299	0.3394	0.0793	0.1557	2.677526	2.068294
2459588	RF_maintenance	100.00%	55.11%	100.00%	0.00%	100.00%	0.00%	35.083973	16.443305	7.304636	105.526032	16.763356	24.992300	10.518083	13.253829	0.4271	0.0882	0.1986	2.630746	1.263125
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	358.584982	358.180876	inf	inf	100.485132	101.878971	569.134387	597.486573	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	98.92%	100.00%	0.00%	100.00%	0.00%	50.362563	20.666981	3.855007	32.649907	4.207990	11.248591	0.539559	6.739542	0.2623	0.0690	0.1283	3.581114	4.201901
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.503893	25.341981	1.752986	11.282013	5.980297	10.266981	-0.141739	4.316140	0.0411	0.0403	0.0026	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	72.387747	27.872625	13.735332	116.751009	31.981246	17.681239	1.630801	12.646876	0.2246	0.0560	0.1110	0.000000	0.000000
2459583	RF_maintenance	100.00%	96.70%	100.00%	0.00%	100.00%	0.00%	49.667934	21.138193	4.793907	36.008192	11.424593	23.071326	-0.607232	0.349197	0.2765	0.0729	0.1286	3.065634	3.024445
2459582	RF_maintenance	100.00%	96.22%	100.00%	0.00%	100.00%	0.00%	43.807026	18.265298	4.559252	32.689655	14.243243	27.924476	-0.635598	0.538806	0.2757	0.0661	0.1365	3.474755	2.878127
2459581	RF_maintenance	100.00%	94.59%	100.00%	0.00%	100.00%	0.00%	58.759614	25.464593	4.615346	36.870321	11.340257	22.454955	-0.388973	0.568497	0.2841	0.0733	0.1351	4.192250	2.837030
2459580	RF_maintenance	100.00%	96.70%	100.00%	0.00%	100.00%	0.00%	44.252196	19.170557	5.203812	37.758345	11.239105	23.646897	-0.692504	0.330289	0.2788	0.0736	0.1322	2.948116	2.927825
2459579	RF_maintenance	100.00%	97.78%	100.00%	0.00%	100.00%	0.00%	44.987468	19.120145	6.177590	42.900723	13.705398	26.748844	0.125346	1.884257	0.2726	0.0694	0.1287	0.000000	0.000000
2459578	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	1.755879	1.596266	1.427021	3.021178	2.140523	0.664809	0.118138	1.936839	0.0506	0.0450	-0.0006	nan	nan
2459577	RF_maintenance	100.00%	97.40%	100.00%	0.00%	100.00%	0.00%	56.050916	24.657707	4.437228	34.468255	13.704242	24.371001	-0.646667	0.553521	0.2664	0.0685	0.1372	3.113220	2.621181
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459575	RF_maintenance	100.00%	66.45%	100.00%	0.00%	100.00%	0.00%	40.399707	19.505695	2.659029	27.419886	6.696800	16.393191	4.166194	6.050249	0.3744	0.0915	0.1753	5.061776	4.015494
2459574	RF_maintenance	100.00%	94.16%	100.00%	0.00%	100.00%	0.00%	40.223158	17.978906	3.018257	26.281611	16.075858	23.996751	0.080228	0.780688	0.2843	0.0669	0.1213	4.244444	3.514783
2459573	RF_maintenance	100.00%	93.56%	100.00%	0.00%	100.00%	0.00%	42.741913	18.483032	6.308973	45.232405	14.125501	27.812029	-0.372633	1.691512	0.2856	0.0691	0.1251	3.826166	3.082067
2459572	RF_maintenance	100.00%	92.43%	100.00%	0.00%	100.00%	0.00%	41.575055	18.720592	3.319467	26.428930	9.992484	17.606760	-0.252366	2.908990	0.2931	0.0736	0.1270	3.904265	1.900311
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	nan	nan
2459570	RF_maintenance	100.00%	90.27%	100.00%	0.00%	100.00%	0.00%	20.984742	25.984207	-0.516763	27.763942	0.780497	1.663865	-0.308951	4.343013	0.2988	0.1180	0.1254	5.387190	20.986519
2459569	RF_maintenance	100.00%	60.06%	100.00%	0.00%	100.00%	0.00%	45.472473	22.022705	3.642503	34.287259	8.759380	10.455159	5.826556	8.804149	0.4143	0.1103	0.1699	4.529640	2.909688
2459566	RF_maintenance	100.00%	95.14%	100.00%	0.00%	100.00%	0.00%	43.892930	17.785905	4.396830	34.296829	12.805806	21.466478	-0.641249	-0.044057	0.2686	0.0603	0.1103	4.219387	2.851198
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-2.008718	-2.008718	-1.878795	-1.878795	-0.888145	-0.888145	-0.944419	-0.944419	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	93.12%	100.00%	0.00%	100.00%	0.00%	46.806384	16.438737	1.015115	36.384703	7.059066	2.292366	0.215367	1.062052	0.2751	0.0718	0.1248	3.417993	2.687267
2459563	RF_maintenance	100.00%	94.00%	100.00%	0.00%	100.00%	0.00%	51.643742	18.467348	7.879643	69.539235	9.463650	22.129740	0.915138	1.823895	0.2764	0.0702	0.1315	3.946972	3.714472
2459562	RF_maintenance	100.00%	93.02%	100.00%	0.00%	100.00%	0.00%	31.282461	11.915511	-0.691072	17.919946	1.101938	2.647246	-0.220051	0.781109	0.2858	0.0736	0.1339	3.920062	2.580181
2459561	RF_maintenance	100.00%	94.10%	100.00%	0.00%	100.00%	0.00%	32.484426	12.413159	-0.552535	17.083467	0.586749	2.896462	0.012991	1.279142	0.2870	0.0752	0.1330	3.595788	2.321233
2459560	RF_maintenance	100.00%	93.51%	100.00%	0.00%	100.00%	0.00%	29.462135	11.447351	-0.650819	17.319021	0.519239	2.903022	0.211330	0.733664	0.2808	0.0719	0.1298	3.629903	2.355524
2459559	RF_maintenance	100.00%	93.46%	100.00%	0.00%	100.00%	0.00%	34.385117	14.584516	-0.479492	18.996424	0.931095	3.348646	0.149559	1.079713	0.2721	0.0731	0.1245	2.912751	2.150114
2459558	RF_maintenance	100.00%	95.08%	100.00%	0.00%	100.00%	0.00%	45.968926	18.973738	4.807759	36.368446	11.108487	23.017306	-0.142026	1.587704	0.2722	0.0713	0.1261	3.141570	2.428529
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0494	0.0381	-0.0019	nan	nan
2459556	RF_maintenance	100.00%	95.19%	100.00%	0.00%	100.00%	0.00%	47.771114	19.537872	5.177116	39.367249	11.857878	20.726303	-0.124186	3.639336	0.2691	0.0733	0.1234	2.980122	1.773109
2459554	RF_maintenance	-	94.54%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.2741	0.0705	0.1277	nan	nan
2459553	RF_maintenance	-	95.67%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.2648	0.0712	0.1244	nan	nan
2459552	RF_maintenance	100.00%	93.51%	100.00%	0.00%	100.00%	0.00%	54.211445	23.339229	7.130853	51.886899	21.701451	31.835650	2.055387	3.193616	0.2676	0.0666	0.1258	3.606241	3.611549
2459551	RF_maintenance	100.00%	92.38%	100.00%	0.00%	100.00%	0.00%	29.135027	11.388237	-0.672334	21.050850	1.244526	4.148735	0.150299	1.241806	0.2810	0.0702	0.1307	3.274359	2.422994
2459550	RF_maintenance	-	97.53%	97.53%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0573	0.0517	-0.0005	nan	nan
2459549	RF_maintenance	100.00%	94.05%	100.00%	0.00%	100.00%	0.00%	42.485662	17.302514	5.237162	39.209829	12.775206	22.631981	0.956451	1.358147	0.2649	0.0671	0.1273	3.815532	3.337730
2459542	RF_maintenance	100.00%	78.08%	100.00%	0.00%	100.00%	0.00%	57.746193	24.259224	8.635775	79.402015	3.939721	1.914212	0.194262	1.339491	0.3252	0.0687	0.1642	2.868604	2.519061
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459540	RF_maintenance	100.00%	76.73%	100.00%	0.00%	100.00%	0.00%	40.900259	16.962119	0.200428	18.103520	7.437326	5.304458	0.135517	0.953829	0.3396	0.0698	0.1649	3.075512	2.172404
2459536	RF_maintenance	100.00%	92.59%	100.00%	0.00%	100.00%	0.00%	71.966449	29.372045	9.762029	67.396220	24.298831	31.491160	-0.718120	2.225608	0.2780	0.0594	0.1212	2.034862	1.221941
2459535	RF_maintenance	100.00%	73.60%	100.00%	0.00%	100.00%	0.00%	31.905323	13.793240	0.039573	16.622172	6.099448	5.662419	0.119591	0.489572	0.3675	0.0736	0.1597	2.388655	1.999762
2459534	RF_maintenance	100.00%	74.50%	100.00%	0.00%	100.00%	0.00%	34.909795	14.648807	-0.503849	15.389101	6.924880	3.934670	-0.048500	0.114444	0.3604	0.0631	0.1259	2.411310	2.470903
2459533	RF_maintenance	100.00%	94.54%	100.00%	0.00%	100.00%	0.00%	52.984162	20.872946	5.133971	36.865498	11.464185	20.748387	-0.108697	1.776666	0.2737	0.0596	0.1067	2.569594	1.663094
2459532	RF_maintenance	100.00%	93.30%	100.00%	0.00%	100.00%	0.00%	60.807744	24.152307	6.985839	49.913755	18.883367	25.369144	-0.690540	0.976329	0.2882	0.0643	0.1089	2.776642	2.638695
2459530	RF_maintenance	100.00%	90.37%	100.00%	0.00%	100.00%	0.00%	33.441828	12.129869	-0.425637	15.593945	2.164187	4.206479	-0.202317	0.585688	0.2927	0.0721	0.1093	3.105142	3.340610
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	0.00%	100.00%	0.00%	100.00%	0.00%	46.954688	28.851234	5.914072	55.628760	31.208748	34.983731	-0.686808	0.606037	0.6554	0.0827	0.4124	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	65.690762	24.274628	8.394754	53.086401	9.552336	29.769023	-2.122941	2.233648	nan	nan	nan	5.008955	4.080589
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.884786	24.904541	7.143200	53.883121	9.410477	23.647211	-0.974837	1.917387	0.2030	0.0693	0.0956	2.081874	1.230766
2459513	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	2.101702	1.741914	1.062851	3.318204	3.675380	0.289249	1.909406	1.461345	0.0567	0.0588	0.0009	nan	nan
2459508	RF_maintenance	100.00%	0.00%	100.00%	0.00%	100.00%	0.00%	43.282760	32.580188	4.133537	52.412108	23.234697	15.638980	10.204161	14.726479	0.6566	0.1041	0.3744	0.000000	0.000000
2459505	RF_maintenance	100.00%	47.37%	100.00%	0.00%	100.00%	0.00%	54.657225	31.009466	6.435348	50.543029	12.211416	10.280318	1.882735	1.851667	0.4204	0.0676	0.2606	20.260991	6.780375
2459503	RF_maintenance	100.00%	0.00%	100.00%	0.00%	100.00%	0.00%	41.452865	30.787055	5.948226	85.490685	37.190472	33.404049	1.034869	3.018107	0.5836	0.0841	0.4219	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 180 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 180, Node 13:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 180: 2459694

Antenna 180: 2459693

Antenna 180: 2459692

Antenna 180: 2459691

Antenna 180: 2459690

Antenna 180: 2459689

Antenna 180: 2459688

Antenna 180: 2459687

Antenna 180: 2459686

Antenna 180: 2459685

Antenna 180: 2459684

Antenna 180: 2459676

Antenna 180: 2459675

Antenna 180: 2459674

Antenna 180: 2459673

Antenna 180: 2459672

Antenna 180: 2459671

Antenna 180: 2459670

Antenna 180: 2459669

Antenna 180: 2459668

Antenna 180: 2459665

Antenna 180: 2459664

Antenna 180: 2459663

Antenna 180: 2459662

Antenna 180: 2459661

Antenna 180: 2459660

Antenna 180: 2459659

Antenna 180: 2459658

Antenna 180: 2459657

Antenna 180: 2459656

Antenna 180: 2459655

Antenna 180: 2459653

Antenna 180: 2459652

Antenna 180: 2459651

Antenna 180: 2459650

Antenna 180: 2459649

Antenna 180: 2459648

Antenna 180: 2459647

Antenna 180: 2459646

Antenna 180: 2459645

Antenna 180: 2459642

Antenna 180: 2459640

Antenna 180: 2459639

Antenna 180: 2459638

Antenna 180: 2459637

Antenna 180: 2459636

Antenna 180: 2459635

Antenna 180: 2459634

Antenna 180: 2459633

Antenna 180: 2459632

Antenna 180: 2459631

Antenna 180: 2459630

Antenna 180: 2459629

Antenna 180: 2459628

Antenna 180: 2459627

Antenna 180: 2459626

Antenna 180: 2459625

Antenna 180: 2459624

Antenna 180: 2459623

Antenna 180: 2459622

Antenna 180: 2459621

Antenna 180: 2459620

Antenna 180: 2459619

Antenna 180: 2459618

Antenna 180: 2459617

Antenna 180: 2459616

Antenna 180: 2459615

Antenna 180: 2459614

Antenna 180: 2459613

Antenna 180: 2459612

Antenna 180: 2459611

Antenna 180: 2459610

Antenna 180: 2459609

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶